Databricks
Get your data ready for AI with Databricks and Incentro. One open platform for data engineering, analytics, governance and AI.
AI is only as good as the data behind it. Databricks brings data, analytics and AI together on a single open platform. It turns fragmented data into something useful, reliable and accessible to everyone who needs it, from data engineers and analysts to AI agents.
Together with Databricks, we help you replace a landscape of data silos with one solid data foundation. So you can do more with your data and, more importantly, turn it into action faster.
Benefits of Databricks
One platform for data and AI
One platform for data and AI Data engineering here, analytics there and AI somewhere else entirely? That quickly becomes an expensive puzzle. Databricks brings data ingestion, processing, analytics, machine learning and AI together on a single platform. Fewer separate tools and integrations, greater cohesion and one foundation to build on.
Reliable data for people and agents
A dashboard can wait until someone spots a mistake. An autonomous AI agent cannot. Unity Catalog lets you centrally manage who and what can access which data, including lineage, auditing and policies. This ensures that people and agents know which data they can use and where it came from.
Open by design
Your data should not be trapped in a single technology stack. Databricks is built around open technologies and data formats such as Delta Lake and Apache Iceberg. This gives you the freedom to combine different tools and clouds and keep developing your architecture without having to rebuild everything from scratch.
From batch to real time
An agent acting on yesterday’s reality is not autonomous. It is simply out of date. Databricks lets you bring batch and streaming data together and process it continuously. This gives analytics, applications and AI agents access to up-to-date information when it matters.
Why Databricks?
Data first, magic second
Everyone wants to do something with AI. But when your data is scattered across databases, applications, spreadsheets and legacy data warehouses, you will eventually run into the same questions: Where is the right data? Can we trust it? Who is allowed to access it? And how do we get it to the right place quickly enough?
Databricks tackles the problem at its source. Its lakehouse architecture combines the scalability and flexibility of a data lake with the reliability and structure of a data warehouse. On top of that, Databricks brings data engineering, analytics, governance and AI together.
The result is not a collection of isolated AI experiments, but a data foundation you can keep building on.
One version of the truth. For your AI agents too.
AI agents need context. That means more than simply having access to data. They also need a consistent understanding of what that data means. Otherwise, your dashboard may use one definition of ‘customer’, finance another, and your agent may happily arrive at a third.
Databricks brings data from different sources together into one shared reality for people, applications and agents. That means everyone bases their analyses, decisions and actions on the same up-to-date information.
This becomes increasingly important as AI grows more autonomous. An agent acting independently does not just need fast access to data. Above all, it needs to understand the right data in the right way.
From data silos to an AI-ready foundation
We do more than help you implement Databricks technology. We take care of everything around it too. We bring your data sources together, design a scalable lakehouse architecture, build reliable data pipelines and make sure governance is properly embedded from day one.
Then the really interesting work can begin: analytics powered by up-to-date data, machine-learning models ready for production and AI agents with the context they need to take real work off your hands.
Ideal for: organisations with fragmented data, legacy data warehouses or complex data pipelines that need a scalable foundation for analytics, AI and agentic AI.
